27358 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 27358 Zip Code | North Carolina | U.S. |
Total Housing Units | 5,432, 100% | 3,742,514 | 116,211,092 |
Utility Gas | 1,700, 31.30%, see rank | 24.68% | 48.85% |
Bottled, Tank, or LP Gas | 811, 14.93%, see rank | 8.00% | 4.86% |
Electricity | 2,536, 46.69%, see rank | 60.27% | 36.68% |
Fuel Oil, Kerosene, etc. | 222, 4.09%, see rank | 4.34% | 5.86% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 135, 2.49%, see rank | 2.17% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 7, 0.13%, see rank | 0.15% | 0.47% |
No Fuel Used | 21, 0.39%, see rank | 0.35% | 1.00% |
ACS 2008-2012 data
| 27358 Zip Code | North Carolina | U.S. |
Total Housing Units | 5,203, 100% | 3,693,221 | 115,226,802 |
Utility Gas | 1,464, 28.14%, see rank | 24.97% | 49.42% |
Bottled, Tank, or LP Gas | 824, 15.84%, see rank | 8.90% | 5.03% |
Electricity | 2,581, 49.61%, see rank | 58.26% | 35.51% |
Fuel Oil, Kerosene, etc. | 257, 4.94%, see rank | 5.24% | 6.46% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.12% |
Wood | 65, 1.25%, see rank | 2.16% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 0, 0.00%, see rank | 0.14% | 0.43% |
No Fuel Used | 12, 0.23%, see rank | 0.29% | 0.90% |
US Census 2000 data
| 27358 Zip Code | North Carolina | U.S. |
Total Housing Units | 3,598, 100% | 3,132,013 | 105,480,101 |
Utility Gas | 671, 18.65%, see rank | 24.19% | 51.22% |
Bottled, Tank, or LP Gas | 586, 16.29%, see rank | 12.59% | 6.52% |
Electricity | 1,859, 51.67%, see rank | 48.81% | 30.35% |
Fuel Oil, Kerosene, etc. | 366, 10.17%, see rank | 11.76% | 8.97% |
Coal or Coke | 0, 0.00%, see rank | 0.01% | 0.14% |
Wood | 108, 3.00%, see rank | 2.10% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 5, 0.14%, see rank | 0.21% | 0.39% |
No Fuel Used | 3, 0.08%, see rank | 0.28% | 0.69% |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.